Senior Specialist, Manufacturing Data Engineering & Digital Integration

Role overview

Technical leadership and integration

• Lead technical initiatives, translate business challenges into architectures and delivery plans, mentor contributors, and review deliverables.
• Design integrations across manufacturing, laboratory, automation, and enterprise systems, including MES, process historians, SCADA/DCS, LIMS/CDS, ERP, and cloud analytics.
• Develop data pipelines, APIs, web services, and integration patterns across OT and IT; define requirements, interface specifications, data models, and architecture decisions.
• Resolve high-impact data-flow, connectivity, interface, and performance issues.
• Own data products from discovery and requirements through prototyping, industrialization, deployment, adoption, and sustainment.

Data platforms and analytics

• Direct configuration and administration of AVEVA PI System, SEEQ, Power BI, data lakes, and cloud analytics environments.
• Prepare, structure, model, and contextualize manufacturing data for dashboards, self-service analytics, advanced analytics, and operational reporting.
• Design reproducible analytical workflows integrating process automation, laboratory, quality, and environmental monitoring data.

AI and regulated delivery

• Lead evaluation, design, and deployment of manufacturing AI/ML solutions for predictive analytics, process monitoring, deviation reduction, and operational efficiency.
• Guide development and integration of AI-powered applications, digital assistants, generative AI, and, where appropriate, computer vision using approved platforms and APIs.
• Assess feasibility, data readiness, model risk, business impact, scalability, and sustainment before industrializing AI solutions.
• Ensure systems follow data governance, data integrity, cybersecurity, and GxP/cGMP requirements.
• Lead SDLC activities, including requirements, design, development or configuration, testing, validation, deployment, release management, change control, and support.
• Lead or support validation and qualification of regulated computerized systems and maintain audit-ready documentation.
• Establish data quality monitoring, metadata, lineage, access, and governance practices.
• Lead delivery for digital, automation, and capital projects involving system integration, data engineering, analytics, or AI.
• Partner with Manufacturing, Engineering, Quality, Technical Operations, Laboratories, IT/OT, vendors, and global digital organizations; communicate technical concepts to varied audiences.

Qualifications

• Bachelor’s degree in data science, computer science, software engineering, data engineering, information systems, computer engineering, engineering, mathematics, statistics, or a related technical or quantitative discipline.
• At least five years of applied experience in data engineering, system integration, manufacturing systems, data analytics, data science, or AI/ML solution development.
• Demonstrated experience leading, mentoring, or directing technical contributors.